Triple
T9997740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Dooley |
E197244
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Jim Dooley |
E197244
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Jim Dooley | Statement: [James Dooley, alsoKnownAs, Jim Dooley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jim Dooley Context triple: [James Dooley, alsoKnownAs, Jim Dooley]
-
A.
Dodd Loyd
Dodd Loyd is an actor known for appearing in the 1985 romantic comedy film "The Slugger’s Wife."
-
B.
William Keene
William Keene was an American character actor known for his numerous supporting roles in mid-20th-century film and television.
-
C.
Jinks Holton
Jinks Holton is a member of the Holton family, known in Virginia for its prominent roles in law, politics, and public service.
-
D.
Clarence Worley
Clarence Worley is the comic book–loving, Elvis-obsessed protagonist of the crime film "True Romance," who impulsively marries a call girl and becomes entangled in a violent, cross-country escapade.
-
E.
James Dooley
chosen
James Dooley is a composer best known for creating dramatic, cinematic music often used in film, television, and trailer scores.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca82f3b61c81908ecc2c1c96dbc2e4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdcc8aa1a881909879a694496f11a5 |
completed | April 2, 2026, 1:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d258439fe88190b17da69f542ecf61 |
completed | April 5, 2026, 12:40 p.m. |
Created at: March 30, 2026, 8:51 p.m.